Abstract
In order to realize the remote control of the meeting documents in progress, the traditional method uses infrared remote control or 2.4 GHz wireless remote control. However, the shortcomings of carrying and storing the remote control, the infrared itself cannot pass through obstacles or the remote control of the device from a large angle, the 2.4 GHz cost is slightly higher, etc., this article introduces the use of PyTorch model and YOLO network gesture control to facilitate this practical problem. The plan proposes to use the PyTorch model to establish a neural network, train to achieve the purpose of classifying gestures, and use the YOLO network to cooperate with the corresponding control algorithm to achieve the purpose of controlling conference documents. The experimental results show that the proposed scheme is feasible and complete to achieve the required functions.
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Acknowledgment
This work is supported in part by National Key R&D Program Funded Project of China under grant number 2018YFB1700200 and 2019YFE0122600, in part by the Hunan Provincial Key Research and Development Project of China under grant numbers 2019GK2133, in part by the Natural Science Foundation of Hunan Province under grant number 2021JJ50050, 2021JJ50058 and 2020JJ6089, in part by the Scientific Research Project of Hunan Provincial Department of Education under grant number 19B147,in part py the Key Project of the Department of Education in Hunan Province (19A133), in part by the Degree and Postgraduate Education Reform Research Project of Hunan Province Department of Education under grant number 2020JGZD059, in part by the Teaching Reform of Ordinary Colleges and Universities Research project of Hunan Province Department of Education under grant number HNJG-2021–0710,in part by the Open PlatformInnovation Foundation of Hunan Provincial Education Department(grant no. 20K046),and this research was supported by the Special Fund Support Project for the Construction of Innovative Provinces in Hunan (2019GK4009).
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Liu, F., Wu, Y., Xiao, F., Liu, Q. (2022). A Dynamic Gesture Recognition Control File Method Based on Deep Learning. In: Khosravi, M.R., He, Q., Dai, H. (eds) Cloud Computing. CloudComp 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-030-99191-3_3
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